Quantifying understory complexity in unmanaged forests using tls and identifying some of its major drivers

  • Dominik Seidel
  • , Peter Annighöfer
  • , Christian Ammer
  • , Martin Ehbrecht
  • , Katharina Willim
  • , Jan Bannister
  • , Daniel P. Soto

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The structural complexity of the understory layer of forests or shrub layer vegetation in open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.

Original languageEnglish
Article number1513
JournalRemote Sensing
Volume13
Issue number8
DOIs
StatePublished - 2 Apr 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Forest structure
  • Old-growth
  • Precipitation gradient
  • Terrestrial laser scanning
  • WorldClim2

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